Short DescriptionAmazon is hiring for Data Scientist who has experience in using Python, R, SAS, SPSS, Matlab or other Statistical / Machine Learning Software.
- Contribute to the development and enhancement of business payment products and features.
- Use data mining, model building, and other analytical techniques to develop and maintain customer segmentation and predictive models to drive the business and improve our machine learning engine.
- Make recommendations for new metrics, techniques, and strategies to improve campaign targeting and measurement.
- Improve targeting capabilities and uncover hidden opportunities using data, analytics and machine learning.
- Understand business and product strategies, goals and objectives. Set the analytics roadmap to drive the goals of the business.
- Own the analytics for one or more product areas, lead planning, execution, and delivery of projects
- Analyze and solve problems at their root, stepping back to understand the broader context.
- Interface with all internal related and ancillary teams to deliver data and analytics as requested.
- Provide support on experimental design, exploratory data analysis, and data management.
- Bachelor's degree in a quantitative area such as math, statistics, computer science, engineering or equivalent experience.
- 3+ years of professional experience in a business environment or an advanced degree in a quantitative field.
- Experience with A/B testing, statistics and model development.
- Proficient in using SQL, ETL, Data Warehouse solutions and databases in a business environment with large-scale, complex datasets.
- Ability to process large data sets from multiple data sources
- Ability to solve complex business problems.
- Graduate degree in Math, Finance, Economics, or Statistics or other related fields from an accredited university.
- Experience in payments, business analysis, strategic consulting, marketing, product management, credit risk or fraud risk.
- Familiarity with text mining, NLP and OCR.
- Experience in complex data cleansing, data validation, and master data management.
- Experience translating analysis results into business recommendations.
- Experience in using Python, R, SAS, SPSS, Matlab or other Statistical / Machine Learning Software.
- Advanced skills in data visualization tools like Quicksight, Tableau or similar BI tools.
- Hands-on experience with statistical analysis and predictive modeling.
- Effective written and verbal communication skills.